Confidence in subjective pain is predicted by reaction time during decision making

Dexmedetomidine versus remifentanil in nasal surgery: a systematic review and meta-analysis

BACKGROUND

Nasal surgeries, addressing anatomical variations for form and function, require careful anesthesia administration, including dexmedetomidine and remifentanil. This meta-analysis evaluates their safety and efficacy variations in nasal surgeries, emphasizing patient comfort and optimal outcomes.

METHODS

Four electronic databases (PubMed, Scopus, Web of Science, and CINAHL Complete) were searched for records in English. Studies that measure the effect of dexmedetomidine versus remifentanil on patients underwent nasal surgery were included. The Cochrane Collaboration's tool was used to assess the quality of the included studies. A random-effect model was preferred and statistical analysis was performed by Stata software version 17.

RESULTS

Out of an initial pool of 63 articles, five studies were selected for this analysis. All of these chosen studies were Randomized Controlled Trials (RCTs). The meta-analysis involved a total of 302 participants, with 152 in the remifentanil group and 150 in the dexmedetomidine group. The analysis aimed to compare the effects of Dexmedetomidine and Remifentanil on heart rate (HR) and mean arterial pressure (MAP) during surgery. Both groups exhibited similar MAP and HR, with the exception of a slightly lower HR in the remifentanil group at the 15th minute of surgery (Standardized Mean Difference: -0.24 [-0.83, 0.34]). Furthermore, when evaluating the impact of these medications on post-surgery outcomes, including pain levels, the use of pain relief medications, patient-surgeon satisfaction, agitation scores, and recovery time, no significant differences were observed between the two medications in any of these aspects.

CONCLUSION

In summary, the study compared Dexmedetomidine and Remifentanil in nasal surgeries anesthesia. No significant differences were found in heart rate, blood pressure, satisfaction, pain, agitation, or recovery time. The study had limitations, and future research should establish standardized protocols and consider various surgical factors.

Human ventromedial prefrontal cortex lesions enhance the effect of expectations on pain perception

Pain is strongly modulated by expectations and beliefs. Across species, subregions of ventromedial prefrontal cortex (VMPFC) are implicated in a variety of functions germane to pain, predictions, and learning. Human fMRI studies show that VMPFC activity tracks expectations about pain and mediates expectancy effects on pain-related activity in other brain regions. Prior lesion studies suggest that VMPFC may instead play a more general role in generating affective responses to painful stimuli. To test whether VMPFC is required to generate affective responses to pain or is more specifically involved in expectancy-based pain modulation, we studied responses to heat stimuli in five adults with bilateral surgical lesions of VMPFC and twenty healthy adults without brain damage. All participants underwent a quantitative sensory testing procedure followed by a pain expectancy task in which cues predicting either low or high pain were followed by intermittent medium intensity heat stimuli. Compared to adults without brain damage, individuals with VMPFC lesions reported larger differences in expected pain based on predictive cues and failed to update expectations following the covert introduction of unexpected medium temperature stimuli. Consistent with observed expectancy differences, subjective pain unpleasantness ratings in the VMPFC lesion group were more strongly modulated by cue during thermal stimulation. We found no group differences in overall pain sensitivity, nor in relationships between pain and autonomic arousal, suggesting that VMPFC damage specifically enhances the effect of expectations on pain processing, likely driven by impaired integration of new sensory feedback to update expectations about pain. These results provide essential new data regarding the specific functional contribution of VMPFC to pain modulation.

How Pain-Related Facial Expressions Are Evaluated in Relation to Gender, Race, and Emotion

Inequities in pain assessment are well-documented; however, the psychological mechanisms underlying such biases are poorly understood. We investigated potential perceptual biases in the judgments of faces displaying pain-related movements. Across five online studies, 956 adult participants viewed images of computer-generated faces (“targets”) that varied in features related to race (Black and White) and gender (women and men). Target identity was manipulated across participants, and each target had equivalent facial movements that displayed varying intensities of movement in facial action-units related to pain (Studies 1–4) or pain and emotion (Study 5). On each trial, participants provided categorical judgments as to whether a target was in pain (Studies 1–4) or which expression the target displayed (Study 5) and then rated the perceived intensity of the expression. Meta-analyses of Studies 1–4 revealed that movement intensity was positively associated with both categorizing a trial as painful and perceived pain intensity. Target race and gender did not consistently affect pain-related judgments, contrary to well-documented clinical inequities. In Study 5, in which pain was equally likely relative to other emotions, pain was the least frequently selected emotion (5%). Our results suggest that perceivers can utilize facial movements to evaluate pain in other individuals, but perceiving pain may depend on contextual factors. Furthermore, assessments of computer-generated, pain-related facial movements online do not replicate sociocultural biases observed in the clinic. These findings provide a foundation for future studies comparing CGI and real images of pain and emphasize the need for further work on the relationship between pain and emotion.

Instructions and experiential learning have similar impacts on pain and pain-related brain responses but produce dissociations in value-based reversal learning

Recent data suggest that interactions between systems involved in higher order knowledge and associative learning drive responses during value-based learning. However, it is unknown how these systems impact subjective responses, such as pain. We tested how instructions and reversal learning influence pain and pain-evoked brain activation. Healthy volunteers (n=40) were either instructed about contingencies between cues and aversive outcomes or learned through experience in a paradigm where contingencies reversed three times. We measured predictive cue effects on pain and heat-evoked brain responses using functional magnetic resonance imaging. Predictive cues dynamically modulated pain perception as contingencies changed, regardless of whether participants received contingency instructions. Heat-evoked responses in the insula, anterior cingulate, and other regions updated as contingencies changed, and responses in the prefrontal cortex mediated dynamic cue effects on pain, whereas responses in the brainstem’s rostroventral medulla (RVM) were shaped by initial contingencies throughout the task. Quantitative modeling revealed that expected value was shaped purely by instructions in the Instructed Group, whereas expected value updated dynamically in the Uninstructed Group as a function of error-based learning. These differences were accompanied by dissociations in the neural correlates of value-based learning in the rostral anterior cingulate, thalamus, and posterior insula, among other regions. These results show how predictions dynamically impact subjective pain. Moreover, imaging data delineate three types of networks involved in pain generation and value-based learning: those that respond to initial contingencies, those that update dynamically during feedback-driven learning as contingencies change, and those that are sensitive to instruction. Together, these findings provide multiple points of entry for therapies designs to impact pain.

Test-Retest Reliability of an Adaptive Thermal Pain Calibration Procedure in Healthy Volunteers

Quantitative sensory testing (QST) allows researchers to evaluate associations between noxious stimuli and acute pain in clinical populations and healthy participants. Despite its widespread use, our understanding of QST’s reliability is limited, as reliability studies have used small samples and restricted time windows. We examined the reliability of pain ratings in response to noxious thermal stimulation in 171 healthy volunteers (n = 99 female, n = 72 male) who completed QST on multiple visits ranging from 1 day to 952 days between visits. On each visit, participants underwent an adaptive pain calibration in which they experienced 24 heat trials and rated pain intensity after stimulus offset on a 0 to 10 Visual Analog Scale. We used linear regression to determine pain threshold, pain tolerance, and the correlation between temperature and pain for each session and examined the reliability of these measures. Threshold and tolerance were moderately reliable (Intra-class correlation = .66 and .67, respectively; P < .001), whereas temperature-pain correlations had low reliability (Intra-class correlation = .23). In addition, pain tolerance was significantly more reliable in female participants than male participants, and we observed similar trends for other pain sensitive measures. Our findings indicate that threshold and tolerance are largely consistent across visits, whereas sensitivity to changes in temperature vary over time and may be influenced by contextual factors.

When does self-report of pain occur?: A study of older adults

Technologies for self-care can drive participatory health and promote independence of older adults. One self-care activity is regularly measuring and registering personal health indicators (self-reporting). Older adults may benefit from this practice, as they are more likely to have chronic health issues and have specific self-monitoring needs. However, self-reporting technologies are usually not designed specifically for them. Pain is usually measured using patient reports compiled during medical appointments, although this process may be affected by memory bias and under reporting of fluctuating pain. To address these issues, we introduced a simple tangible interface to self-report pain levels and conducted a three-hour evaluation with 24 older adults. The goal of this study was to identify whether specific activities, activity levels or pain levels trigger older adults to self-report their pain level, besides to understand how older adults would use such a device. Within the limited time frame of the experiment, the majority of our participants chose to report pain when they felt it most, not reporting lower levels of pain. No evidence was found to suggest a relationship between the reporting of pain and the activity (or activity level). Several design insights intended to improve the design of technologies are provided.

User-Centric Design Methodology for mHealth Apps. The PainApp Paradigm for Chronic Pain

The paper presents a user-centric methodology in order to design successful mobile health (mHealth) applications. In addition to the theoretical background, such an example is presented with an application targeting chronic pain. The pain domain was decided due to its significance in many aspects: its complexity, dispersion in the population, the financial burden it causes, etc. The paper presents a step-by-step plan in order to build mobile health applications. Participatory design and interdisciplinarity are only some of the critical issues towards the desired result. In the given example (development of the PainApp), a participatory design was followed with a team of seventeen stakeholders that drove the design and development phases. Three physicians, one behavioral scientist, three IT and UX experts, and ten patients collaborated together to develop the final solution. The several features implemented in the PainApp solution are presented in details. The application is threefold: it supports the management, reporting, and treatment effectiveness monitoring. The paper is giving details on the methodological approach while presenting insights on the actual plan and the steps followed for having a patient-centric solution. Key success factors and barriers to mobile health applications that support the need for such an approach are also presented.

Human Decision Time in Uncertain Binary Choice

Decision time, also known as choice reaction time, has been frequently discussed in the field of psychology. The Hick–Hyman Law (HHL) has been a fundamental model that has revealed the quantitative relationship between the mean choice reaction time of human and the information entropy of stimuli. However, the HHL is only focused on rule-based behavior in which rules for selecting response according to stimulus are certain and neglects to model the knowledge-based behavior in which choices are uncertain and influenced by human belief. In this article, we explored the decision time related to one basic knowledge-based behavior—uncertain binary choice, where selections of response are determined by human belief degrees but not by stimuli uncertainties. Two experiments were conducted: one for verifying the HHL and the other for uncertain binary choice. The former (experiment) demonstrated the effectiveness of the HHL, and the latter one indicated that there is an exponential relationship existing between decision time and entropy of belief degree in uncertain binary choice. Moreover, data obtained from both experiments showed that the disturbance term of decision time should not be seen as probabilistic as existing studies have assumed, which highlighted the necessity and advantage of uncertain regression analysis.